static int calculateWeightDifference(NeuralCryptography X, NeuralCryptography Y)
{
int difference = 0;
for (int i = 0; i < X.K * X.N - 1; i++)
{
difference = difference + Math.Abs(X.w[i] - Y.w[i]);
}
return(difference);
}
private void button1_Click_1(object sender, EventArgs e)
{
dgv_A.Rows.Clear();
dgv_B.Rows.Clear();
int K = (int)nud_K.Value,
N = (int)nud_N.Value,
L = (int)nud_L.Value;
object[] dataA = new object[K * N];
object[] dataB = new object[K * N];
for (int i = 0; i < N; i++)
{
dgv_A.Columns.Add("", "");
dgv_B.Columns.Add("", "");
}
NeuralCryptography A = new NeuralCryptography(K, L, N);
NeuralCryptography B = new NeuralCryptography(K, L, N);
InputVector inpV = new InputVector();
A.IntAll();
B.IntAll();
A.RandomWeight(false);
B.RandomWeight(true);
int difference = calculateWeightDifference(A, B);
string result = "Failed";
int steps = 0;
while (difference != 0)
{
inpV.inputVector(K * N);
A.CountOutput(inpV.input);
B.CountOutput(inpV.input);
if (A.output == B.output)
{
A.UpdateWeights(inpV.input);
B.UpdateWeights(inpV.input);
difference = calculateWeightDifference(A, B);
dgv_A.Rows.Clear();
dgv_B.Rows.Clear();
for (int i = 0; i < K; i++)
{
for (int j = 0; j < N; j++)
{
{
dataA[j] = A.w[i * N + j];
dataB[j] = B.w[i * N + j];
}
}
dgv_A.Rows.Add(dataA);
dgv_B.Rows.Add(dataB);
}
//this.Refresh();
if (difference == 0)
{
result = "Success";
break;
}
}
steps++;
}
int key_size = _string.Length / (A.L * 2 + 1);
int key_length = A.K * A.N / key_size;
for (int i = 1; i < key_length; i++)
{
int k = 1;
for (int j = (i - 1) * key_size; j < i * key_size - 1; j++)
{
k = k + A.w[j] + A.L;
txt_Key.Text = txt_Key.Text + _string[k];
}
}
txt_Status.Text = "Status:" + result + "\r\n Number of iterations:" + steps;
}
